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Intelligent Algorithms for Analysis and Control of Dynamical Systems
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Intelligent Algorithms for Analysis and Control of Dynamical SystemsНазвание: Intelligent Algorithms for Analysis and Control of Dynamical Systems
Автор: Rajesh Kumar, V.P. Singh
Издательство: Springer
Серия: Algorithms for Intelligent Systems
Год: 2021
Страниц: 202
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Discusses various intelligent algorithms for analysis and control of dynamical systems.

This book explores various intelligent algorithms including evolutionary algorithms, swarm intelligence-based algorithms for analysis and control of dynamical systems. Both single-input–single-output (SISO) and multi-input–multi-output (MIMO) systems are explored for analysis and control purposes. The applications of intelligent algorithm vary from approximation to optimal control design. The applications of intelligent algorithms not only improve understanding of a dynamical system but also enhance the control efficacy. The intelligent algorithms are now readily applied to all fields of control including linear control, nonlinear control, digital control, optimal control, etc. The book also discusses the main benefits attained due to the application of algorithms to analyze and control.

There are mainly three algorithms used for training the ANNs, namely Bayesian regularization (BR), scaled conjugate gradient (SCG), and Levenberg–Marquardt (LM), out of which BR and SCG algorithms are considered as effective. So, this paper uses those two algorithms to implement the proposed ANN-PID controller. SCG is one of the best conjugate gradient methods, which is widely used for the feed-forward neural networks. SCG uses the second-order approximation for step size and search direction, which varies it from general optimization strategy. Optimal distance is calculated by iterative approach.

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